Context-aware data caching for 5G heterogeneous small cells networks

Zheng Chang, Yunan Gu, Zhu Han, Xianfu Chen, Tapani Ristaniemi

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    39 Citations (Scopus)


    In this work, we investigate the problem of context-aware data caching in the heterogeneous small cell networks (HSCNs) to provide satisfactory to the end-users in reducing the service latency. In particular, we explore the storage capability of base stations (BSs) in HSCNs and propose a data caching model consists of edge caching elements (CAEs), small cell base stations (SBSs), and macro cell BS (MBS). Then, we concentrate on how to efficiently match the data contents to the different cache entities in order to minimize the overall system service latency. We model it as a distributed college admission (CA) stable matching problem and tackle this issue by utilizing contextual information to generate the preference lists of cache entities and contents, respectively. In the CA model, we leverage the resident-oriented Gale-Shapley (RGS) algorithm to find a stable matching between the contents and the cache entities. Through numerical results, we illustrate the advantages of of our proposed methods.
    Original languageEnglish
    Title of host publicationCommunications (ICC), 2016 IEEE International Conference on
    PublisherIEEE Institute of Electrical and Electronic Engineers
    ISBN (Electronic)978-1-4799-6664-6
    ISBN (Print)978-1-4799-6665-3
    Publication statusPublished - 14 Jul 2016
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Conference on Communications, ICC 2016: Communications for All Things - Kuala Lumpur, Malaysia
    Duration: 23 May 201627 May 2016


    ConferenceIEEE International Conference on Communications, ICC 2016
    Abbreviated titleICC 2016
    CityKuala Lumpur


    • matching
    • small cell networks
    • context aware
    • content caching


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